Installation#

PyPI release#

The latest tagged release is available on PyPI and can be installed with pip. We recommend using an isolated environment (venv, micromamba or conda):

python -m venv .venv        # optional but encouraged
source .venv/bin/activate
pip install gato-hep

The base install targets CPU execution and pulls the matching TensorFlow/TensorFlow-Probability versions automatically. Optional extras:

pip install "gato-hep[gpu]"   # CUDA-enabled TensorFlow wheels
pip install "gato-hep[dev]"   # linting + testing helpers for development

When using the gpu extra make sure the host already provides compatible NVIDIA drivers and CUDA libraries.

Editable install from source#

To track main or contribute patches, install the repository in editable mode:

git clone https://github.com/FloMau/gato-hep.git
cd gato-hep
python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"

You can append [gpu] to the extras list if you need the CUDA stack in the same environment (pip install -e ".[dev,gpu]").

Post-install check#

Confirm that the package imports correctly and report the version:

python -c "import gatohep; print(f'gato-hep version {gatohep.__version__} installed.')"

Environment compatibility#

  • Python >=3.10.

  • TensorFlow 2.17 – 2.19 and TensorFlow-Probability >=0.24 (installed automatically through the dependency metadata).

  • ml_dtypes >= 0.4.1.

If pip cannot find compatible TensorFlow wheels (e.g. on Apple Silicon), install the platform-specific tensorflow-macos / tensorflow-metal packages first and then re-run pip install gato-hep. See the official TensorFlow release notes for detailed platform guidance.